Discovering disease-associated genes in weighted protein-protein interaction networks

作者：Cui, Ying^*; Cai, Meng; Stanley, H. Eugene

来源：Physica A: Statistical Mechanics and Its Applications , 2018, 496: 53-61.

DOI：10.1016/j.physa.2017.12.080

• Disease gene discovering
• Topological properties
• Weighted PPI network
• Machine learning

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

• 出版日期2018-4-15
• 单位西安电子科技大学